Abstract

We examine the influence of the morphology-density relation and a wide range of simple models for biased galaxy formation on statistical measures of large-scale structure. We contrast the behavior of local biasing models, in which the efficiency of galaxy formation is determined by the density, geometry, or velocity dispersion of the local mass distribution, with that of nonlocal biasing models, in which galaxy formation is modulated coherently over scales larger than the galaxy correlation length. If morphological segregation of galaxies is governed by a local morphology-density relation, then the correlation function of E/S0 galaxies should be steeper and stronger than that of spiral galaxies on small scales, as observed, while on large scales the E/S0 and spiral galaxies should have correlation functions with the same shape but different amplitudes. Similarly, all of our local bias models produce scale-independent amplification of the correlation function and power spectrum in the linear and mildly nonlinear regimes; only a nonlocal biasing mechanism can alter the shape of the power spectrum on large scales. Moments of the biased galaxy distribution retain the hierarchical pattern of the mass moments, but biasing alters the values and scale dependence of the hierarchical amplitudes S3 and S4. Pair-weighted moments of the galaxy velocity distribution are sensitive to the details of the bias prescription even if galaxies have the same local velocity distribution as the underlying dark matter. The nonlinearity of the relation between galaxy density and mass density depends on the biasing prescription and the smoothing scale, and the scatter in this relation is a useful diagnostic of the physical parameters that determine the bias. While the assumption that galaxy formation is governed by local physics leads to some important simplifications on large scales, even local biasing is a multifaceted phenomenon whose impact cannot be described by a single parameter or function. The sensitivity of galaxy clustering statistics to the details of galaxy biasing is an obstacle to testing cosmological models, but it is an equally significant asset for testing physical theories of galaxy formation against data from redshift and peculiar velocity surveys.

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